Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.14279/29528
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Mellit, Adel | - |
dc.contributor.author | Kalogirou, Soteris A. | - |
dc.date.accessioned | 2023-06-28T08:33:01Z | - |
dc.date.available | 2023-06-28T08:33:01Z | - |
dc.date.issued | 2022-01-01 | - |
dc.identifier.isbn | 9780128206416 | - |
dc.identifier.uri | https://hdl.handle.net/20.500.14279/29528 | - |
dc.description.abstract | Handbook of Artificial Intelligence Techniques in Photovoltaic Systems: Modelling, Control, Optimization, Forecasting and Fault Diagnosis provides readers with a comprehensive and detailed overview of the role of artificial intelligence in PV systems. Covering up-to-date research and methods on how, when and why to use and apply AI techniques in solving most photovoltaic problems, this book will serve as a complete reference in applying intelligent techniques and algorithms to increase PV system efficiency. Sections cover problem-solving data for challenges, including optimization, advanced control, output power forecasting, fault detection identification and localization, and more. Supported by the use of MATLAB and Simulink examples, this comprehensive illustration of AI-techniques and their applications in photovoltaic systems will provide valuable guidance for scientists and researchers working in this area. | en_US |
dc.language.iso | en | en_US |
dc.rights | Copyright © Elsevier B.V. | en_US |
dc.subject | Artificial Intelligence Techniques | en_US |
dc.subject | Photovoltaic Systems | en_US |
dc.title | Handbook of Artificial Intelligence Techniques in Photovoltaic Systems: Modeling, Control, Optimization, Forecasting and Fault Diagnosis | en_US |
dc.type | Book | en_US |
dc.collaboration | Cyprus University of Technology | en_US |
dc.subject.category | Mechanical Engineering | en_US |
dc.journals | Subscription | en_US |
dc.country | Cyprus | en_US |
dc.subject.field | Engineering and Technology | en_US |
dc.publication | Peer Reviewed | en_US |
dc.identifier.doi | 10.1016/C2019-0-00960-0 | en_US |
dc.identifier.scopus | 2-s2.0-85136621495 | - |
dc.identifier.url | https://api.elsevier.com/content/abstract/scopus_id/85136621495 | - |
cut.common.academicyear | 2022-2023 | en_US |
dc.identifier.spage | 1 | en_US |
dc.identifier.epage | 358 | en_US |
item.openairetype | book | - |
item.cerifentitytype | Publications | - |
item.fulltext | No Fulltext | - |
item.grantfulltext | none | - |
item.openairecristype | http://purl.org/coar/resource_type/c_2f33 | - |
item.languageiso639-1 | en | - |
crisitem.author.dept | Department of Mechanical Engineering and Materials Science and Engineering | - |
crisitem.author.faculty | Faculty of Engineering and Technology | - |
crisitem.author.orcid | 0000-0002-4497-0602 | - |
crisitem.author.parentorg | Faculty of Engineering and Technology | - |
Appears in Collections: | Βιβλία/Books |
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